1. Architectural Design Communicating: Big Picture Holistically Gestalt

2. Why is the Architectural Design Important? Constitutes and “intellectually graspable” model of the system. Hides complexity. Enables communication among all stakeholders Highlights design decisions: system and subsystem interfaces and context, data dependencies, and user interaction

3. Data Design Principles Define data early: it is natural to think about what a system should do (function) and how it will do it (behavior), be sure to also consider what information (data) is required to start, continue and persist. Fully identify data’s structure Represent data objects as classes (i.e., attributes and operations) Refine the data model later Enforce information hiding and functional independence Use pre-built ADTs as available Prefer a programming language which supports OO concepts

4. Architectural Styles and Patterns Style Influences entire system Four Parts Components Connecters (interfaces) Constraints on components and their interaction/integration Semantic models Common Styles: data-centered, data-flow, call-and-return (hierarchical), object-oriented, layered Pattern Influences a part of the system (less broad than style) Modifies/constrains style and focuses on subsystem behavior Common Patterns: concurrency (o/s-type, discrete event), persistence (database, system state), distributed computing (blackboard, broker-based)

5. Additional Points of Emphasis Questions for assessing the suitability of an architectural style (pg 255 7/e, pgs 265-266 6/e) Architectural context diagrams (see figure 9.5 7/e, figure 10.5 6/e) Read Summary (especially paragraph 3 pg 273 7/e, para 4 pgs 288-289 6/e)